In 2020, we (albeit unexpectedly) were forced to move our infrastructure to support a remote workforce. In turn, 2021 compelled us to address how we collaborate and best work together in this new landscape. Now, in 2022, we can expect to see the priority shifting to the security of our new (and potentially vulnerable) networks. Combined with the continuing problem of ever-growing data challenges and privacy concerns, IT professionals will have their work cut out for them in 2022. Here is a peek at some of the things that may impact your business in the upcoming year.
Anyone in the IT industry knows that malware, cybersecurity, and other threats are increasing, and attacks are becoming more mature. Data growth is a big concern for 2022, but protecting your data should be one of your organization’s highest priorities. Because the “traditional” security perimeter is all but gone due to employees working remotely on a large-scale basis, this will lead organizations to make decisions that will have them viewing their security from a different angle. Organizations should be doing their best to respond to these attacks before they happen, where possible. Cybersecurity mesh, by definition, is a flexible architecture that brings together best of breed, standalone security solutions to work together to improve overall security.
The trick to cybersecurity mesh is understanding what level of security you want to have and how to get there from where you are now. The thought here is that organizations that adopt a cybersecurity mesh strategy will have integrated security that will allow for a productive, cooperative, and secure infrastructure and this will allow for a reduction of the costs involved when an isolated security attack occurs.
Data is one of those things that is forever growing, and because of this, solutions are always required for simplification of said data, as well as complete access to it. Making clean and organized data available from multiple access points will remain on the list of technology priorities but finding this solution in a cost-effective manner is the continual roadblock. Considering the amount of data that grows year over year while dealing with the fact that skilled professionals in the data and analytics field remains relatively constant, finding appropriate people within an organization to handle this growth is a regular challenge. Data fabric is a 2022 trend, which effectively has been renamed with a new buzzword that is the most recent in a long line of trends that address the issue of “How do we deal with a constant data explosion in the most economical way?”
Loss of customer trust as a consequential result from privacy incidents and dealing with data protection and privacy legislation on the international stage is going to be, if it is not already, a priority for CIOs in 2022. Protection of personal and otherwise sensitive information from an IT department, whether it be a data issue or on a software or hardware level, and the analysis of infrastructures and allowing for information to be shared securely without violating confidentiality is the current landscape of concern over security. The main concern is, “How do we change our employees’ online behavior to keep our company protected from privacy legislation?”
Cloud-native platforms use cloud computing to give organizations elastic and scalable capabilities to deliver faster value and reduced costs to the bottom line. Although this trend is something already in play in most organizations, it still has a lot of traction left, especially where organizations are trying to change their applications to be more resilient and manageable.
Information technology professionals need to utilize great effort to integrate AI within applications. This is accomplished with the Internet of Things, as well as AI engineering to operationalize artificial intelligence models. Unfortunately, there is a perception that as much as this is a valuable place to spend IT budget, many of these projects waste money and time on projects that never quite make it to the infrastructure. Also, many organizations do also have a hard time showing and retaining value from these solutions. AI engineering is an integrated approach for operationalizing AI models.
One artificial intelligence technique is generative AI—machine learning approaches that learn about content and uses said data to create code and targeted marketing. This should be employed delicately, as it also opens the door to fraud and identity issues if not kept in check.
If you are concerned about these, or any other IT trends, please contact your Connection Account Manager. They can connect you with one of the skilled technology professional experts to help you to navigate the choppy waters of technology indecision and help put you on a path with the best possible move-forward strategy.